A mathematical model of atherosclerosis with reverse cholesterol transport and associated risk factors.

Atherosclerosis, the leading cause of death in the US, is a disease in which a plaque builds up inside the arteries. The low density lipoprotein (LDL) and high density lipoprotein (HDL) concentrations in the blood are commonly used to predict the risk factor for plaque growth. In a recent paper (Hao and Friedman in Plos One e90497, 2014), we have developed a mathematical model of plaque growth which includes the (LDL, HDL) concentrations. In the present paper, we have refined that model by including the effect of reverse cholesterol transport. By exploration-by-examples of regression of a plaque in mice, our model simulations suggest that such drugs as used for mice may also slow plaque growth in humans. We next proceeded to explore the effects of oxidative stress or antioxidant deficiency, high blood pressure and cigarette smoking as risk factors. We suggest for an individual in one of these three risk categories and with specified (LDL, HDL) concentration, how to reduce or eliminate the risk of atherosclerosis.